Therapeutic management and haemato-biochemical changes in canine hepatozoonosis
Bibliographic record
Abstract
A seven-year-old Labrador retriever dog was presented to VetLab Meerut with a history of vomiting, anorexia, fever and weakness for 15 days. Clinical examination revealed pyrexia, pale conjunctival and oral mucous membranes. Haemato-biochemical evaluation revealed anemia (Hb-8.4g/dl, RBC-4.25 106/µl, PCV-28.2%), leukocytosis (23.32×103/µl), thrombocytopenia (1.62 lakhs/µl), hypoalbuminemia (1.83 g/dl), hyperglobulinemia (4.91 g/dl) and elevated levels of blood urea nitrogen (BUN) (48.2 mg/dl), creatinine (3.12 mg/dl), alanine aminotransferase (ALT) (121.3 U/L) and aspartate aminotransferase (AST) (69.6U/L). On blood smear examination Hepatozoon canis gamonts in the neutrophils were found. Subsequently, animal was treated with a combination therapy including single dose of Inj. Imidocarb dipropionate (6.6 mg/kg, SC) and Tab. Doxycycline (5 mg/kg, PO, BID) for 21 days. Supportive treatment was done with antiemetics, hepatoprotectants, hematinics, plasma expanders and acaricides. An uneventful recovery was noticed after 21 days of treatment. Our present report highlights the successful effect of combination therapy including imidocarb dipropionate and doxycycline drugs, fighting against the infection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".